The Carpentries training program aims to improve data literacy and reproducible science. IMCI sponsors the University of Idaho as a member in the organization.

Four workshops will be offered this spring for upper-level undergraduate students, new graduate students and anyone else interested in good-practices in data management and analysis.

STUDENTS wishing to take the workshops for credit need to register via the UI course schedule for any combination of BCB 503 01, BCB 503 02, and/or BCB 503 03. U of I registration deadlines apply.

ALL PARTICIPANTS, regardless of academic credit, must register with IMCI to attend. Space is limited. A limited number of in person seats will be offered. An online option may also be available. IMCI registration will close one week prior to the workshop.

R for Reproducible Scientific Analysis (1 cr)


BCB 503-01 (CRN 43945) or AVS 503 (CRN 44936)

Instructors: James Van Leuven (I), Breanna Sipley (I)

November 1, 2-4:30 pm
November 2, 8-4 pm
November 3, 2-4:30 pm

Course Title: WS: R for Reproducible Science

Course Description: Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation in R. This introductory course will showcase reproducible research through simple analysis examples. The goal is to teach novice programmers to write modular code and best practices for using R for data analysis. This short hands-on course will give participants a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching basic programming in R, and will not teach statistical analysis. No prior knowledge of R or RStudio is needed.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that you can install software on (e.g., have admin rights). Please ensure you have the latest version of R and RStudio installed on your machine.

Version Control (2 cr)


BCB 503-02 (CRN 44933) or AVS 503 (CRN 44937)

Instructors: Breanna Sipley (I), Luke Harmon (I), James Van Leuven (H)

Course Title: WS: Version Control

Oct 17 – Dec 16, Mondays, 2:30-6 pm

Course Description: In this course, students will learn how to use version control and test-driven design to create and maintain biological software. Students will learn how to break down problems associated with processing and analyzing large, cumbersome datasets into a set of manageable requirements; how to implement software process tools such as version control and test-driven design in R to confidently write robust code that meets these requirements, and how to efficiently and effectively teach these skills to others.

Data Visualization in R and Python (1 cr)


BCB 503-03 (CRN 44933) or AVS 503 (CRN 44932)

Instructors: James Van Leuven (I), Chava Castaneda (I), Clint Elg (I), Akorede Seriki (I), Kristen Martinet (I/H) 

Nov 29 – Dec 8, T/Th, 2-4:30 pm

Course Title: WS: Data Vis in R and Python

Course Description: Data Carpentries aims to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This hands-on workshop will cover the use of the R and python programming languages for visualizing complex data and making pretty figures. The course is aimed at graduate students and other researchers, but is open to all and is designed for learners that have no prior experience in programming. However, some experience in R or Python may be useful. Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that you can install software on (e.g., have admin rights). Please ensure you have the latest version of R and RStudio installed on your machine.